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Causal contribution of primate auditory cortex to auditory perceptual decision-making

Nature Neuroscience volume 19, pages 135–142 (2016)Cite this article

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An Erratum to this article was published on 29 March 2016

This article has been updated

Abstract

Auditory perceptual decisions are thought to be mediated by the ventral auditory pathway. However, the specific and causal contributions of different brain regions in this pathway, including the middle-lateral (ML) and anterolateral (AL) belt regions of the auditory cortex, to auditory decisions have not been fully identified. To identify these contributions, we recorded from and microstimulated ML and AL sites while monkeys decided whether an auditory stimulus contained more low-frequency or high-frequency tone bursts. Both ML and AL neural activity was modulated by the frequency content of the stimulus. But, only the responses of the most stimulus-sensitive AL neurons were systematically modulated by the monkeys' choices. Consistent with this observation, microstimulation of AL, but not ML, systematically biased the monkeys' behavior toward the choice associated with the preferred frequency of the stimulated site. Together, these findings suggest that AL directly and causally contributes sensory evidence to form this auditory decision.

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Figure 1: Stimuli and task.
Figure 2: Psychophysical performance on the low-high task.
Figure 3: Recording locations and ML and AL tonotopy.
Figure 4: Neuronal sensitivity to stimulus frequency and coherence in ML (top) and AL (bottom).
Figure 5: Relationship between neurometric and psychometric sensitivity for ML (top) and AL (bottom).
Figure 6: Relationship between choice probability and neurometric sensitivity for ML (top) and AL (bottom).
Figure 7: Effect of microstimulation on behavioral performance during the low-high task for ML (top) and AL (bottom).

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Change history

  • 23 December 2015

    In the version of this article initially published, the neurometric slope values in the bottom panel of Figure 4a were given as 1.6, 1.0., 1.0; the correct values are 0.8, 0.5, 0.5. The x axes in Figure 4b, right panel, were numbered 0 to 3; the correct range is 0 to 1.5. The segments of the traces in Figure 6b–d with significant regression coefficients were gray; they should have been red. And the top segment of the bar for 0–10% in the bottom panel of Figure 7c was blue; it should have been pink. The errors have been corrected in the HTML and PDF versions of the article.

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Acknowledgements

We thank H. Hersh for helpful suggestions on the preparation of this manuscript and H. Shirley for outstanding veterinary support. This research was supported by grants from the National Eye Institute (J.I.G.), National Institute on Deafness and Other Communication Disorders (Y.E.C.) and the Boucai Hearing Restoration Fund (Y.E.C.).

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Author notes

  1. Joshua I Gold and Yale E Cohen: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Otorhinolaryngology, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Joji Tsunada, Andrew S K Liu & Yale E Cohen

  2. Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Joshua I Gold & Yale E Cohen

  3. Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Yale E Cohen

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  1. Joji Tsunada
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Contributions

J.T., A.S.K.L., J.I.G. and Y.E.C. designed the study and wrote the paper. J.T. and A.S.K.L. collected the experimental data. J.T., J.I.G. and Y.E.C. analyzed the data.

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Correspondence to Yale E Cohen.

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Integrated supplementary information

Supplementary Figure 1 Relationship between choice probability and neurometric sensitivity when including both single-unit (45 from ML and 55 from AL) and multi-unit (10 from ML and 12 from AL) data.

a, Distributions of choice probabilities calculated from firing rates between stimulus onset and the inferred time of the decision commitment (i.e., the end of the decision time plus an additional 50 ms). Black bars indicate H0: choice probability≠0.5, p<0.05 (permutation test). Arrows indicate median values. b, c, d, Time-dependent correlations between neuron-by-neuron choice probability and neurometric sensitivity (i.e., slope), plotted relative to stimulus onset (b), the inferred time of the decision commitment (c), and the inferred time of movement initiation (d). Significant regression coefficients are highlighted in red (Spearman correlation coefficient, p<0.05). The horizontal bars represent the range of the inferred times of the decision commitment, for high (<-80% and >+80%, black), middle (-80% to -20% and +80% to +20%, dark gray), and low (-20% to +20%, light gray) coherence. e, Scatterplot examples showing the correlation between neurometric slope and choice probability for each monkey. These plots were generated from the time point with the largest correlation in AL for each monkey.

Supplementary Figure 2 Ideal-observer analysis of ML (top) and AL (bottom) sensitivity to stimulus coherence.

ROC-based neuronal selectivity (expressed as the expected percentage of correct responses from the ideal observer) for preferred versus non-preferred stimuli at different coherences is shown for each populations of recorded neurons. ROC values were computed in 100-ms sliding time bins offset by 10 ms. Thick/thin lines indicate mean/s.e.m. High coherence (<−80% and >+80%) is shown in black, middle coherence (−80% to −20% and +80% to +20%) in dark grey, and low coherence (−20% to +20%) in light grey. ROC values that differ significantly (t-test, p <0.05) from 0.5 are colored red.

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Tsunada, J., Liu, A., Gold, J. et al. Causal contribution of primate auditory cortex to auditory perceptual decision-making. Nat Neurosci 19, 135–142 (2016). https://doi.org/10.1038/nn.4195

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